Algorithm of Multi-camera Object Handoff Based on Object Mapping

2017 ◽  
pp. 575-582
Author(s):  
Jianrong Cao ◽  
Xuemei Sun ◽  
Zhenyu Li ◽  
Yameng Wang
Keyword(s):  
Object Mapping

scholarly journals Multiellipsoidal Mapping Algorithm

2018 ◽  
Vol 8 (8) ◽  
pp. 1239 ◽  
Author(s):  
Carlos Villaseñor ◽  
Nancy Arana-Daniel ◽  
Alma Alanis ◽  
Carlos Lopez-Franco ◽  
Javier Gomez-Avila
Keyword(s):  
Point Clouds ◽  
Mapping Algorithm ◽  
Robotic Mapping ◽  
Wide Range ◽  
Important Challenge ◽  
Memory Cost ◽  
Environmental Representation ◽  
Object Shapes ◽  
Quadratic Surfaces ◽  
Object Mapping

The robotic mapping problem, which consists in providing a spatial model of the environment to a robot, is a research topic with a wide range of applications. One important challenge of this problem is to obtain a map that is information-rich (i.e., a map that preserves main structures of the environment and object shapes) yet still has a low memory cost. Point clouds offer a highly descriptive and information-rich environmental representation; accordingly, many algorithms have been developed to approximate point clouds and lower the memory cost. In recent years, approaches using basic and “simple” (i.e., using only planes or spheres) geometric entities for approximating point clouds have been shown to provide accurate representations at low memory cost. However, a better approximation can be implemented if more complex geometric entities are used. In the present paper, a new object-mapping algorithm is introduced for approximating point clouds with multiple ellipsoids and other quadratic surfaces. We show that this algorithm creates maps that are rich in information yet low in memory cost and have features suitable for other robotics problems such as navigation and pose estimation.

scholarly journals Do the Eyes Have It? A Systematic Review on the Role of Eye Gaze in Infant Language Development

2021 ◽  
Vol 11 ◽  
Author(s):  
Melis Çetinçelik ◽  
Caroline F. Rowland ◽  
Tineke M. Snijders
Keyword(s):  
Systematic Review ◽  
Language Development ◽  
Language Learning ◽  
Speech Processing ◽  
Eye Gaze ◽  
Gaze Following ◽  
Object Mapping ◽  
Attentional Cues ◽  
Gaze Cues

Eye gaze is a ubiquitous cue in child–caregiver interactions, and infants are highly attentive to eye gaze from very early on. However, the question of why infants show gaze-sensitive behavior, and what role this sensitivity to gaze plays in their language development, is not yet well-understood. To gain a better understanding of the role of eye gaze in infants' language learning, we conducted a broad systematic review of the developmental literature for all studies that investigate the role of eye gaze in infants' language development. Across 77 peer-reviewed articles containing data from typically developing human infants (0–24 months) in the domain of language development, we identified two broad themes. The first tracked the effect of eye gaze on four developmental domains: (1) vocabulary development, (2) word–object mapping, (3) object processing, and (4) speech processing. Overall, there is considerable evidence that infants learn more about objects and are more likely to form word–object mappings in the presence of eye gaze cues, both of which are necessary for learning words. In addition, there is good evidence for longitudinal relationships between infants' gaze following abilities and later receptive and expressive vocabulary. However, many domains (e.g., speech processing) are understudied; further work is needed to decide whether gaze effects are specific to tasks, such as word–object mapping or whether they reflect a general learning enhancement mechanism. The second theme explored the reasons why eye gaze might be facilitative for learning, addressing the question of whether eye gaze is treated by infants as a specialized socio-cognitive cue. We concluded that the balance of evidence supports the idea that eye gaze facilitates infants' learning by enhancing their arousal, memory, and attentional capacities to a greater extent than other low-level attentional cues. However, as yet, there are too few studies that directly compare the effect of eye gaze cues and non-social, attentional cues for strong conclusions to be drawn. We also suggest that there might be a developmental effect, with eye gaze, over the course of the first 2 years of life, developing into a truly ostensive cue that enhances language learning across the board.

scholarly journals Human-Guided Object Mapping for Task Transfer

2018 ◽  
Vol 7 (2) ◽  
pp. 1-24 ◽  
Author(s):  
Tesca Fitzgerald ◽  
Ashok Goel ◽  
Andrea Thomaz
Keyword(s):  
Task Transfer ◽  
Object Mapping

scholarly journals Multi-View Instance Matching with Learned Geometric Soft-Constraints

2020 ◽  
Vol 9 (11) ◽  
pp. 687
Author(s):  
Ahmed Samy Nassar ◽  
Sébastien Lefèvre ◽  
Jan Dirk Wegner
Keyword(s):  
Ground Level ◽  
Learning Task ◽  
Image Features ◽  
Geometric Constraints ◽  
Lighting Conditions ◽  
Instance Matching ◽  
Candidate Image ◽  
Image Appearance ◽  
One Step ◽  
Object Mapping

We present a new approach for matching urban object instances across multiple ground-level images for the ultimate goal of city-scale mapping of objects with high positioning accuracy. What makes this task challenging is the strong change in view-point, different lighting conditions, high similarity of neighboring objects, and variability in scale. We propose to turn object instance matching into a learning task, where image-appearance and geometric relationships between views fruitfully interact. Our approach constructs a Siamese convolutional neural network that learns to match two views of the same object given many candidate image cut-outs. In addition to image features, we propose utilizing location information about the camera and the object to support image evidence via soft geometric constraints. Our method is compared to existing patch matching methods to prove its edge over state-of-the-art. This takes us one step closer to the ultimate goal of city-wide object mapping from street-level imagery to benefit city administration.

scholarly journals Failure to learn from feedback underlies word learning difficulties in toddlers at risk for autism

2012 ◽  
Vol 40 (1) ◽  
pp. 29-46 ◽  
Author(s):  
R. BEDFORD ◽  
T. GLIGA ◽  
K. FRAME ◽  
K. HUDRY ◽  
S. CHANDLER ◽  
...  
Keyword(s):  
At Risk ◽  
Word Learning ◽  
Children With Autism ◽  
Social Feedback ◽  
Term Retention ◽  
Vocabulary Building ◽  
Referent Selection ◽  
Long Term Retention ◽  
Object Mapping

ABSTRACTChildren's assignment of novel words to nameless objects, over objects whose names they know (mutual exclusivity; ME) has been described as a driving force for vocabulary acquisition. Despite their ability to use ME to fast-map words (Preissler & Carey, 2005), children with autism show impaired language acquisition. We aimed to address this puzzle by building on studies showing that correct referent selection using ME does not lead to word learning unless ostensive feedback is provided on the child's object choice (Horst & Samuelson, 2008). We found that although toddlers aged 2;0 at risk for autism can use ME to choose the correct referent of a word, they do not benefit from feedback for long-term retention of the word–object mapping. Further, their difficulty using feedback is associated with their smaller receptive vocabularies. We propose that difficulties learning from social feedback, not lexical principles, limits vocabulary building during development in children at risk for autism.

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